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Related Experiment Video

Updated: Mar 19, 2026

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps

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Published on: July 19, 2024

Progressive Backmapping of Highly Coarse-Grained Protein Models.

Yu Zhu¹, Jacob M Remington², Shenghan Song¹

¹Borch Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN 47907.

Biorxiv : the Preprint Server for Biology

|March 18, 2026

Summary

This summary is machine-generated.

This study introduces a progressive backmapping framework for reconstructing all-atom (AA) models from coarse-grained (CG) simulations. The method accurately details complex biomolecular assemblies, including viral particles, across multiple resolutions.

Keywords:

backmapping coarse graining multi-domain proteins mutant neural network virus-like particle

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Published on: March 1, 2022

Area of Science:

Computational Biology
Molecular Dynamics
Biophysics

Background:

Reconstructing all-atom (AA) structures from coarse-grained (CG) models is crucial for multiscale molecular dynamics (MD) simulations of large biomolecular assemblies.
Current methods struggle with mesoscale systems beyond conventional MD reach.

Purpose of the Study:

To develop a progressive backmapping framework for accurate AA structure reconstruction from CG models.
To enable detailed analysis of complex mesoscale biomolecular systems.

Main Methods:

Introduced a stepwise, progressive backmapping approach building upon neural-network-based ProNet Backmapping.
Implemented reconstruction across neighboring resolutions (e.g., 3-residue-per-site HCG to AA).
Applied hierarchical reconstruction to complex protein assemblies and viral particles.

Main Results:

Achieved high accuracy in reconstructing AA models for diverse proteins and flexible linkers.
Successfully reconstructed large, complex protein assemblies, including multiple virus-like particles.
Demonstrated hierarchical backmapping of entire viral assemblies from HCG to AA resolution across three levels.

Conclusions:

The progressive backmapping framework offers a scalable solution for incorporating atomistic detail into mesoscale simulations.
This method advances the study of complex biological systems in chemistry and biology.